Relationship matching of data sources: A graph-based approach

Abstract

Relationship matching is a key procedure during the process of transforming structural data sources, like relational data bases, spreadsheets into the common data model. The matching task refers to the automatic identification of correspondences between relationships of source columns and the relationships of the common data model. Numerous techniques have been developed for this purpose. However, the work is missing to recognize relationship types between entities in information obtained from data sources in instance level and resolve ambiguities. In this paper, we develop a method for resolving ambiguous relationship types between entity instances in structured data. The proposed method can be used as standalone matching techniques or to complement existing relationship matching techniques of data sources. The result of an evaluation on a large real-world data set demonstrated the high accuracy of our approach (>80%).